History of Artificial Intelligence

The next seven years after the Dartmouth conference were very significant in the advancement of AI with a number of significant researches and inventions made. In 1957, Newell and Simon constructed the first version of The General Problem Solver (GPS). This program was an extension of Wiener’s feedback principle but possessed enhance capabilities to solve a greater extent of common sense problems. In 1958, John McCarthy completed the development of LISP (List Processing) language, which quickly became the language of choice among AI researchers and development and still is use today. Furthermore in 1963, MIT secured a multi million grant through which the concept of cognition was deeply explored.

The 1970s brought forward the system built on the concept of Expert systems. These systems predicted the probability of a solution until a preset set of conditions. The advancement in computer technology in the previous years played significant contributions toward the popularity of Expert Systems. The large capacity of the computers at that time meant that the expert system in 1970s had the potential to formulate rules and interpret statistics. In the next ten years from the time Expert system were introduced, expert systems were introduced to make forecast for stock market, aiding doctors in diagnosing a disease as well assisting miners in finding promising mineral locations. During the 1970s, many new methods in the development of AI were proposed. For example, David Marr proposed theories about machine vision on the topic of distinguishing an image which has been based on the shading of another image as well as basic information on shapes, colors, textures and edges. Another significant development during the 1970s was the PROLOGUE language.

By 1980, AI research was moving at a fast pace and had found a strong foothold in industry as well. Experts system in particular was in high demand because of their efficiency. Industries leaders such as DuPont, General Motors and Boeing were heavily relying on the expert system to keep up with their business demands. It also gave boost to companies developing AI systems, such a Teknowledge and Intellicorp which specialized in producing software to aid in the production of expert systems. Other fields of AI also made their presence felt in the market. One of these fields was Machine Vision. The work done by researchers in 1970s became the foundation of industrial devices such as cameras and computers on assembly lines, which performed quality control. Machine Vision algorithms were used in these devices to find out the differences between object using black and white differences. The field of AI faced a significant setback during the late 1980s and it suffered a loss of almost half a billion dollars. There were severe cutting in research funding and a number of large scale projects, such as the Smart Truck project funded by Defense Advanced Research Project Agency, were cancelled. Despite these discouraging events, AI slowly made progress, with new technology being continuously developed in Japan. Fuzzy Logic, which was first pioneered in the US, was put to use because it has the capability of making decisions under uncertain conditions. Neural Networks were also extensively looked into as a possible ways to achieve the artificial intelligence. The 1980s era was significant to AI in the sense that it introduced AI to the industry and corporate marketplace and also shows that the technology had real life uses and would be the key in the next century.